Targeting cells with single vectors using multiple-feature Boolean logic

Lief E Fenno; Joanna Mattis; Charu Ramakrishnan; Minsuk Hyun; Soo Yeun Lee; Miao He; Jason Tucciarone; Aslihan Selimbeyoglu; Andre Berndt; Logan Grosenick; Kelly A Zalocusky; Hannah Bernstein; Haley Swanson; Chelsey Perry; Ilka Diester; Frederick M Boyce; Caroline E Bass; Rachael Neve; Z Josh Huang; Karl Deisseroth

doi:10.1038/nmeth.2996

Targeting cells with single vectors using multiple-feature Boolean logic

Nat Methods. 2014 Jul;11(7):763-72. doi: 10.1038/nmeth.2996. Epub 2014 Jun 8.

Authors

Lief E Fenno¹, Joanna Mattis¹, Charu Ramakrishnan², Minsuk Hyun³, Soo Yeun Lee⁴, Miao He⁵, Jason Tucciarone⁶, Aslihan Selimbeyoglu⁷, Andre Berndt³, Logan Grosenick⁸, Kelly A Zalocusky⁹, Hannah Bernstein¹⁰, Haley Swanson¹¹, Chelsey Perry¹¹, Ilka Diester¹², Frederick M Boyce¹³, Caroline E Bass¹⁴, Rachael Neve¹⁵, Z Josh Huang⁵, Karl Deisseroth¹⁶

Affiliations

¹ 1] Department of Neuroscience, Stanford University, Stanford, California, USA. [2] Department of Bioengineering, Stanford University, Stanford, California, USA. [3].
² 1] Department of Bioengineering, Stanford University, Stanford, California, USA. [2].
³ Department of Bioengineering, Stanford University, Stanford, California, USA.
⁴ 1] Department of Bioengineering, Stanford University, Stanford, California, USA. [2] CNC Program, Stanford University, Stanford, California, USA.
⁵ Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA.
⁶ 1] Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. [2] Program in Neuroscience, Stony Brook University, Stony Brook, New York, USA.
⁷ Department of Neuroscience, Stanford University, Stanford, California, USA.
⁸ 1] Department of Neuroscience, Stanford University, Stanford, California, USA. [2] Department of Bioengineering, Stanford University, Stanford, California, USA. [3] CNC Program, Stanford University, Stanford, California, USA.
⁹ 1] Department of Neuroscience, Stanford University, Stanford, California, USA. [2] CNC Program, Stanford University, Stanford, California, USA.
¹⁰ Department of Neuroscience and Physiology, New York University School of Medicine, New York, New York, USA.
¹¹ CNC Program, Stanford University, Stanford, California, USA.
¹² 1] Department of Bioengineering, Stanford University, Stanford, California, USA. [2] Ernst Struengmann Institute for Neuroscience, Frankfurt, Germany.
¹³ Department of Neurology, Massachusetts General Hospital, Cambridge, Massachusetts, USA.
¹⁴ Department of Pharmacology and Toxicology, School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, New York, USA.
¹⁵ Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
¹⁶ 1] Department of Bioengineering, Stanford University, Stanford, California, USA. [2] CNC Program, Stanford University, Stanford, California, USA. [3] Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA. [4] Howard Hughes Medical Institute, Stanford University, Stanford, California, USA.

Abstract

Precisely defining the roles of specific cell types is an intriguing frontier in the study of intact biological systems and has stimulated the rapid development of genetically encoded tools for observation and control. However, targeting these tools with adequate specificity remains challenging: most cell types are best defined by the intersection of two or more features such as active promoter elements, location and connectivity. Here we have combined engineered introns with specific recombinases to achieve expression of genetically encoded tools that is conditional upon multiple cell-type features, using Boolean logical operations all governed by a single versatile vector. We used this approach to target intersectionally specified populations of inhibitory interneurons in mammalian hippocampus and neurons of the ventral tegmental area defined by both genetic and wiring properties. This flexible and modular approach may expand the application of genetically encoded interventional and observational tools for intact-systems biology.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Animals
Bacterial Proteins / genetics
Dependovirus / genetics
Female
Gene Targeting / methods*
Genetic Vectors*
HEK293 Cells
Hippocampus / metabolism
Humans
Integrases / metabolism
Interneurons / physiology*
Introns
Logic
Luminescent Proteins / genetics
Male
Mice
Mice, Transgenic
Promoter Regions, Genetic
Transgenes

Substances

Bacterial Proteins
Luminescent Proteins
yellow fluorescent protein, Bacteria
Cre recombinase
Integrases

Abstract

Publication types

MeSH terms

Substances

Grants and funding